Make Your Own Neural Network A Gentle Journey Through The Mathematics Of Neural Networks And Making Your Own Using The Python


Make Your Own Neural Network A Gentle Journey Through The Mathematics Of Neural Networks And Making Your Own Using The Python
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Make Your Own Neural Network


Make Your Own Neural Network
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Author : Tariq Rashid
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2016

Make Your Own Neural Network written by Tariq Rashid and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with Application software categories.


This book is for anyone who wants to understand what neural network[s] are. It's for anyone who wants to make and use their own. And it's for anyone who wants to appreciate the fairly easy but exciting mathematical ideas that are at the core of how they work. This guide is not aimed at experts in mathematics or computer science. You won't need any special knowledge or mathematical ability beyond school maths [sic] ... Teachers can use this guide as a particularly gentle explanation of neural networks and their implementation to enthuse and excite students making their very own learning artificial intelligence with only a few lines of programming language code. The code has been tested to work with a Raspberry Pi, a small inexpensive computer very popular in schools and with young students"--(page 6, Introduction)



Knowledge Discovery In The Social Sciences


Knowledge Discovery In The Social Sciences
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Author : Prof. Xiaoling Shu
language : en
Publisher: Univ of California Press
Release Date : 2020-02-04

Knowledge Discovery In The Social Sciences written by Prof. Xiaoling Shu and has been published by Univ of California Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-04 with Social Science categories.


Knowledge Discovery in the Social Sciences helps readers find valid, meaningful, and useful information. It is written for researchers and data analysts as well as students who have no prior experience in statistics or computer science. Suitable for a variety of classes—including upper-division courses for undergraduates, introductory courses for graduate students, and courses in data management and advanced statistical methods—the book guides readers in the application of data mining techniques and illustrates the significance of newly discovered knowledge. Readers will learn to: • appreciate the role of data mining in scientific research • develop an understanding of fundamental concepts of data mining and knowledge discovery • use software to carry out data mining tasks • select and assess appropriate models to ensure findings are valid and meaningful • develop basic skills in data preparation, data mining, model selection, and validation • apply concepts with end-of-chapter exercises and review summaries



Information Technology New Generations


Information Technology New Generations
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Author : Shahram Latifi
language : en
Publisher: Springer
Release Date : 2018-04-12

Information Technology New Generations written by Shahram Latifi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-12 with Computers categories.


This volume presents a collection of peer-reviewed, scientific articles from the 15th International Conference on Information Technology – New Generations, held at Las Vegas. The collection addresses critical areas of Machine Learning, Networking and Wireless Communications, Cybersecurity, Data Mining, Software Engineering, High Performance Computing Architectures, Computer Vision, Health, Bioinformatics, and Education.



Make Your Own Neural Network An In Depth Visual Introduction For Beginners


Make Your Own Neural Network An In Depth Visual Introduction For Beginners
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Author : Michael Taylor
language : en
Publisher: Independently Published
Release Date : 2017-10-04

Make Your Own Neural Network An In Depth Visual Introduction For Beginners written by Michael Taylor and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-04 with Computers categories.


A step-by-step visual journey through the mathematics of neural networks, and making your own using Python and Tensorflow. What you will gain from this book: * A deep understanding of how a Neural Network works. * How to build a Neural Network from scratch using Python. Who this book is for: * Beginners who want to fully understand how networks work, and learn to build two step-by-step examples in Python. * Programmers who need an easy to read, but solid refresher, on the math of neural networks. What's Inside - 'Make Your Own Neural Network: An Indepth Visual Introduction For Beginners' What Is a Neural Network? Neural networks have made a gigantic comeback in the last few decades and you likely make use of them everyday without realizing it, but what exactly is a neural network? What is it used for and how does it fit within the broader arena of machine learning? we gently explore these topics so that we can be prepared to dive deep further on. To start, we'll begin with a high-level overview of machine learning and then drill down into the specifics of a neural network. The Math of Neural Networks On a high level, a network learns just like we do, through trial and error. This is true regardless if the network is supervised, unsupervised, or semi-supervised. Once we dig a bit deeper though, we discover that a handful of mathematical functions play a major role in the trial and error process. It also becomes clear that a grasp of the underlying mathematics helps clarify how a network learns. * Forward Propagation * Calculating The Total Error * Calculating The Gradients * Updating The Weights Make Your Own Artificial Neural Network: Hands on Example You will learn to build a simple neural network using all the concepts and functions we learned in the previous few chapters. Our example will be basic but hopefully very intuitive. Many examples available online are either hopelessly abstract or make use of the same data sets, which can be repetitive. Our goal is to be crystal clear and engaging, but with a touch of fun and uniqueness. This section contains the following eight chapters. Building Neural Networks in Python There are many ways to build a neural network and lots of tools to get the job done. This is fantastic, but it can also be overwhelming when you start, because there are so many tools to choose from. We are going to take a look at what tools are needed and help you nail down the essentials. To build a neural network Tensorflow and Neural Networks There is no single way to build a feedforward neural network with Python, and that is especially true if you throw Tensorflow into the mix. However, there is a general framework that exists that can be divided into five steps and grouped into two parts. We are going to briefly explore these five steps so that we are prepared to use them to build a network later on. Ready? Let's begin. Neural Network: Distinguish Handwriting We are going to dig deep with Tensorflow and build a neural network that can distinguish between handwritten numbers. We'll use the same 5 steps we covered in the high-level overview, and we are going to take time exploring each line of code. Neural Network: Classify Images 10 minutes. That's all it takes to build an image classifier thanks to Google! We will provide a high-level overview of how to classify images using a convolutional neural network (CNN) and Google's Inception V3 model. Once finished, you will be able to tweak this code to classify any type of image sets! Cats, bats, super heroes - the sky's the limit.



Deep Learning For Business With Python


Deep Learning For Business With Python
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Author : N. Lewis
language : en
Publisher:
Release Date : 2016-10-27

Deep Learning For Business With Python written by N. Lewis and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-27 with categories.


Leverage Deep Learning for Business Analysis - with Python! Deep Learning for Business With Python takes you on a gentle, fun and unhurried journey to building your own deep neural network models for business use in Python. It demystifies deep learning by taking a how-to approach through a series of business case studies. Using plain language, it offers a simple, intuitive, practical, non-mathematical, easy to follow guide to the most successful ideas, outstanding techniques and usable solutions available using Python. QUICK AND EASY: Deep Learning for Business With Python offers the ideal introduction to deep learning for business analysis. It is designed to be accessible. It will teach you, in simple and easy-to-understand terms, how to take advantage of deep learning to enhance business outcomes using Python. NO EXPERIENCE?: I'm assuming you never did like linear algebra, don't want to see things derived, dislike complicated computer code, and you're here because you want to see how to use deep neural networks for business problems explained in plain language, and try them out for yourself. THIS BOOK IS FOR YOU IF YOU WANT: Explanations rather than mathematical derivation Real world applications that make sense. Illustrations to deepen your understanding. Worked examples you can easily follow and immediately implement. Ideas you can actually use and try on your own data. TAKE THE SHORTCUT: Through a simple to follow process you will learn how to build deep neural network models for business problems using Python. Once you have mastered the process, it will be easy for you to translate your knowledge into your own powerful business applications. Each chapter covers, step by step, a different aspect of deep neural networks. You get your hands dirty as you work through some challenging real world business issues. YOU'LL LEARN HOW TO: Unleash the power of Deep Neural Networks for classifying Insurance Claims. Develop hands on solutions to predict product yield. Design successful applications for modeling customer churn. Master techniques for efficient classification in peer to peer marketplaces. Deploy deep neural networks to predict crash injury severity. Adopt winning solutions to forecast property value. Everything you need to get started is contained within this book. Deep Learning for Business with Python is your very own hands on practical, tactical, easy to follow guide to mastery. Buy this book today, your next big breakthrough using deep neural networks is only a page away!



Developers Guide For Building Own Neural Network Library


Developers Guide For Building Own Neural Network Library
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Author : Venish Patidar
language : en
Publisher: Venish Patidar
Release Date : 2022-10-01

Developers Guide For Building Own Neural Network Library written by Venish Patidar and has been published by Venish Patidar this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-01 with Computers categories.


This book contains everything that a curious mind seeks more. The book sets the seeker on the mathematical journey, which starts with the biological neuron and a network and ends by creating your own. The book will gently introduce the concept of imitation and the roots of neural networks. Firstly, it will introduce the working of a biological neuron, followed by the analogies with the artificial neurons. After an overview of those, the book will shift the gears from biology to mathematics. We will find our way of creating the neural network library with the help of mathematics and developing the code alongside the section.



Deep Learning For Business With R


Deep Learning For Business With R
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Author : N. Lewis
language : en
Publisher:
Release Date : 2016-08-31

Deep Learning For Business With R written by N. Lewis and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-31 with categories.


Master Deep Learning & Leverage Business Analytics - the Easy Way! Deep Learning for Business With R takes you on a gentle, fun and unhurried journey to building your own deep neural network models for business use in R. Using plain language, it offers an intuitive, practical, non-mathematical, easy to follow guide to the most successful ideas, outstanding techniques and usable solutions available using R. BUSINESS ANALYTICS FAST! This book is an ideal introduction to deep learning for business analytics. It is designed to be accessible. It will teach you, in simple and easy-to-understand terms, how to take advantage of deep learning to enhance business outcomes. NO EXPERIENCE REQUIRED I'm assuming you never did like linear algebra, don't want to see things derived, dislike complicated computer code, and you're here because you want to see how to use deep neural networks for business problems explained in plain language, and try them out for yourself. THIS BOOK IS FOR YOU IF YOU WANT: Explanations rather than mathematical derivation Real world applications that make sense. Illustrations to deepen your understanding. Worked examples in R you can easily follow and immediately implement. Ideas you can actually use and try on your own data. QUICK AND EASY: Deep Learning is little more than using straight-forward steps to process data into actionable insight. And in Deep Learning for Business with R, author Dr. N.D Lewis will show you how that's done. It's easier than you think. Through a simple to follow process you will learn how to build deep neural network models for business problems in R. Once you have mastered the process, it will be easy for you to translate your knowledge into your own powerful business applications. TAKE THE SHORTCUT: R is easy to use, available on all major operating systems and free! Each chapter covers, step by step, a different aspect of deep neural networks. You get your hands dirty as you work through some challenging real world business issues. YOU'LL LEARN HOW TO: Unleash the power of Deep Neural Networks for classifying the popularity of online news stories.. Develop hands on solutions for assessing customer churn.. Design successful applications for modeling customer brand choice. Master techniques for efficient product demand forecasting. Deploy deep neural networks to predict credit card expenditure. Adopt winning solutions to forecast the value of automobiles. ACCELERATE YOUR PROGRESS If you want to accelerate your progress and act on what you have learned, this book is the place to get started. It reveals how deep neural networks work, and takes you under the hood with an easy to follow process showing you how to build them faster than you imagined possible using the powerful and free R programming language. Everything you need to get started is contained within this book. Deep Learning for Business With R is your very own hands on practical, tactical, easy to follow guide to mastery Buy this book today your next big breakthrough using deep neural networks is only a page away!



Entwicklung Eines Verfahrens Zur Ermittlung Des Schadenausma Es An Geb Uden Auf Basis Von Fotografie Und Laserscanning Technologie Unter Verwendung Von K Nstlicher Intelligenz


Entwicklung Eines Verfahrens Zur Ermittlung Des Schadenausma Es An Geb Uden Auf Basis Von Fotografie Und Laserscanning Technologie Unter Verwendung Von K Nstlicher Intelligenz
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Author : Ibrahim Halabi
language : de
Publisher: BoD – Books on Demand
Release Date : 2021-01-01

Entwicklung Eines Verfahrens Zur Ermittlung Des Schadenausma Es An Geb Uden Auf Basis Von Fotografie Und Laserscanning Technologie Unter Verwendung Von K Nstlicher Intelligenz written by Ibrahim Halabi and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-01 with Technology & Engineering categories.


Die Möglichkeiten für eine Bestimmung des Zerstörungsausmaßes in Gebieten, welche durch Naturkatastrophen oder durch Menschen herbeigeführte Zerstörungen betroffen wurden, hängen von der Art bzw. Schwere der Ereignisse, wie zum Beispiel Erdbeben, Hurrikane oder Kriege, sowie von den Zerstörungsbereichen, wie zum Beispiel Gebäuden und Infrastrukturen, ab. Ein Gesamtbild des Zerstörungsausmaßes stellt im Endeffekt einen notwendigen Schritt für die späteren richtigen Maßnahmen dar, welche zum stabilen Wiederaufbau führen. Diese Forschungsarbeit befasst sich ausschließlich mit der Ermittlung des Schadengrads an Gebäuden im Einzelnen oder in kleinen Gruppen und nicht mit der Schadenermittlung anderer Arten von betroffenen Bereichen, wie zum Beispiel Wälder oder Infrastrukturen. Sie stellt aber einen wichtigen Ansatz für weitere Entwicklung mit dem Ziel einer genaueren Betrachtung des Schadenausmaßes in dem gesamten betroffenen Gebiet dar und dient gleichzeitig zur Kooperation bei der Auswertung der Ergebnisse von anderen Diensten sowie Software, die andere Schäden an Gebäudekonstruktionen und Infrastrukturen ermitteln.



Neural Network Tutorials Herong S Tutorial Examples


Neural Network Tutorials Herong S Tutorial Examples
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Author : Herong Yang
language : en
Publisher: HerongYang.com
Release Date : 2021-03-06

Neural Network Tutorials Herong S Tutorial Examples written by Herong Yang and has been published by HerongYang.com this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-06 with Computers categories.


This book is a collection of notes and sample codes written by the author while he was learning Neural Networks in Machine Learning. Topics include Neural Networks (NN) concepts: nodes, layers, activation functions, learning rates, training sets, etc.; deep playground for classical neural networks; building neural networks with Python; walking through Tariq Rashi's 'Make Your Own Neural Network' source code; using 'TensorFlow' and 'PyTorch' machine learning platforms; understanding CNN (Convolutional Neural Network), RNN (Recurrent Neural Network), GNN (Graph Neural Network). Updated in 2023 (Version v1.22) with minor updates. For latest updates and free sample chapters, visit https://www.herongyang.com/Neural-Network.



Neural Networks


Neural Networks
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Author : Steven Cooper
language : en
Publisher: Roland Bind
Release Date : 2018-11-06

Neural Networks written by Steven Cooper and has been published by Roland Bind this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-06 with Computers categories.


☆★The Best Neural Networks Book for Beginners★☆ If you are looking for a complete beginners guide to learn neural networks with examples, in just a few hours, then you need to continue reading. Have you noticed the increasing prevalence of software that tries to learn from you? More and more, we are interacting with machines and platforms that try to predict what we are looking for. From movie and television show recommendations on Netflix based on your taste to the keyboard on your smartphone trying to predict and recommend the next word you may want to type, it's becoming obvious that machine learning will definitely be part of our future. If you are interested in learning more about the computer programs of tomorrow then, Understanding Neural Networks – A Practical Guide for Understanding and Programming Neural Networks and Useful Insights for Inspiring Reinvention is the book you have been waiting for. ★★ Grab your copy today and learn ★★ ♦ The history of neural networks and the way modern neural networks work ♦ How deep learning works ♦ The different types of neural networks ♦ The ability to explain a neural network to others, while simultaneously being able to build on this knowledge without being COMPLETELY LOST ♦ How to build your own neural network! ♦ An effective technique for hacking into a neural network ♦ Some introductory advice for modifying parameters in the code-based environment ♦ And much more... You'll be an Einstein in no time! And even if you are already up to speed on the topic, this book has the power to illustrate what a neural network is in a way that is capable of inspiring new approaches and technical improvements. The world can't wait to see what you can do! Most of all, this book will feed the abstract reasoning region of your mind so that you are able to theorize and invent new types and styles of machine learning. So, what are you waiting for? Scroll up and click the buy now button to learn everything you need to know in no time!